13 papers
AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation
Qingda Hu, Ziheng Qiu, Jieru Zhao +2
Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons. However, existing IL-based v…
Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments
Jie Jia, Yaofeng Su, Zeyu Bao +4
Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches either overestimate risk ba…
Rhythm: Learning Interactive Whole-Body Control for Dual Humanoids
Hongjin Chen, Wei Zhang, Pengfei Li +10
Realizing interactive whole-body control for multi-humanoid systems is critical for unlocking complex collaborative capabilities in shared environments. Although recent advancement…
Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
Zhihua Hua, Junli Wang, Pengfei LI +6
Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…
Collaborative Learning of Local 3D Occupancy Prediction and Versatile Global Occupancy Mapping
Shanshuai Yuan, Julong Wei, Muer Tie +3
Vision-based 3D semantic occupancy prediction is vital for autonomous driving, enabling unified modeling of static infrastructure and dynamic agents. Global occupancy maps serve as…
CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots
Shihao Ma, Hongjin Chen, Zijun Xu +6
For effective deployment in real-world environments, humanoid robots must autonomously navigate a diverse range of complex terrains with abrupt transitions. While the Vanilla mixtu…